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Investigator:

Daniel E. Acuña

Abstract

This project identifies scientists and organizations and their topical interests, enabling the tracking of past productivity and impact. By linking scholarly literature and grants, this project creates a unified dataset that captures diverse scientific disciplines and federal grant award types. A web-based levels the playing field for scientists lacking knowledge about research and funding programs. Users are expected to spend less time searching the literature and more time evaluating significance and impact.

This project consolidates disparate repositories of publications and grants, disambiguates and enriches information about scientists and organizations, and builds a web-based tool to help navigate this information. This project solves many of these issues by modeling the relationship approximately 2.6 million grants from the Federal RePORTER, and a consolidated, multi-source dataset of millions of articles from Microsoft Academic Graph (83 M), MEDLINE (25 M), PubMed Open Access Subset (1 M), ArXiv (0.6 M), and the National Bureau of Economic Research [NBER] (14K). The project creates a web-based tool that generates instantaneous reports about publications, grants, scientists, and organizations related to users’ interests. The unified dataset and web tool could revolutionize how Program Officers evaluate proposals and how researchers find fundable ideas, making science faster, more accurate, and less biased.